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README.md
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# Plan_Q-RAG
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## Setup Rent GPU
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Git
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```bash
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git clone https://github.com/griver/Q-RAG.git
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cd Q-RAG
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#Only need when you don't have your self-trained model
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git clone https://huggingface.co/Q-RAG/qrag-ft-e5-on-hotpotqa
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```
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Environment Setup
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python -c "from rl.agents.pqn import PQNActor; print('✅ Q-RAG installed successfully')"
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```
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```bash
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cd ..
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python train_q_rag_logt.py \
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envs=hotpotqa \
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algo=pqn_e5_hotpotqa \
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eval_interval=50 \ #original 100
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envs_parallel=1 \
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max_action_length=220
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python train_q_rag.py \
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envs=hotpotqa \
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algo=pqn_e5_hotpotqa \
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# Plan_Q-RAG
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## Setup Rent GPU
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Git datasets for Q-RAG
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```bash
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git clone https://huggingface.co/datasets/Q-RAG/Hotpotqa_and_Musique
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cd Hotpotqa_and_Musique
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unzip hotpotqa+musique.zip -d /workspace/datasets
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cd ..
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rm -rf Hotpotqa_and_Musique
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du -h
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```
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Git repo of Q-RAG
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```bash
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git clone https://github.com/griver/Q-RAG.git
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cd Q-RAG
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#Only need when you don't have your self-trained hotpotqa model yet
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git clone https://huggingface.co/Q-RAG/qrag-ft-e5-on-hotpotqa
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```
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Environment Setup
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python -c "from rl.agents.pqn import PQNActor; print('✅ Q-RAG installed successfully')"
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```
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Train: Log with Time
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```bash
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python train_q_rag_logt.py \
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envs=hotpotqa \
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algo=pqn_e5_hotpotqa \
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eval_interval=50 \ #original 100
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envs_parallel=1 \
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max_action_length=220
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```
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Original Train
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```bash
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python train_q_rag.py \
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envs=hotpotqa \
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algo=pqn_e5_hotpotqa \
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